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Identifying tweets of personal health experience through word embedding and LSTM neural network
BACKGROUND: As Twitter has become an active data source for health surveillance research, it is important that efficient and effective methods are developed to identify tweets related to personal health experience. Conventional classification algorithms rely on features engineered by human domain ex...
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| Publicado no: | BMC Bioinformatics |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5998756/ https://ncbi.nlm.nih.gov/pubmed/29897323 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-018-2198-y |
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